Software Listens for Hints of Depression

Software Listens for Hints of Depression

Signal processing: Researchers at Cogito Health are developing mathematical models to detect vocal cues that may signal depression. The last graph represents the software’s confidence level in determining depression, from the beginning to the end of a vocal recording. In this example, the data shows a very high likelihood of depression.

It’s a common complaint in any communication breakdown: “It’s not what you said, it’s how you said it.” For professor Sandy Pentland and his group at MIT’s Media Lab, the tone and pitch of a person’s voice, the length and frequency of pauses and speed of speech can reveal much about his or her mood.

While most speech recognition software concentrates on turning words and phrases into text, Pentland’s group is developing algorithms that analyze subtle cues in speech to determine whether someone is feeling awkward, anxious, disconnected or depressed.

Cogito Health, a company spun out of MIT based in Charlestown, MA, is building on Pentland’s research by developing voice-analysis software to screen for depression over the phone.

For years, psychiatrists have recognized a characteristic pattern in the way that many people with clinical depression speak: slowly, quietly and often in a halting monotone. Company CEO Joshua Feast and his colleagues are training computers to recognize such vocal patterns in audio samples.

Feast says the software could be a valuable tool in managing patients with chronic diseases, which often lead to depression. As part of certain disease-management programs, nurses routinely call patients between visits to ask if they are taking their medication. However, symptoms of depression are more difficult for nurses to identify. Feast says voice analysis software could provide a natural and noninvasive way for nurses to screen for depression during routine phone calls. “If you’re a nurse and you’re trying to deal with a patient with long-term diabetes, it’s very hard to tell if a person is depressed,” says Feast. “We try to help nurses detect possible mood disorders in patients that have chronic disease.”

A few years ago, the pharmaceutical giant Pfizer developed voice-analysis software to detect early signs of Parkinson’s disease. Pfizer scientists designed the software to recognize tiny tremors in speech. Such tremors offered clues to help gauge patients’ response to various medications.

In much the same way, Cogito Health’s software detects specific patterns in vocal recordings. For example, the researchers have developed mathematical models to measure a speaker’s consistency in tone, fluidity of speech, level of vocal energy, and level of engagement in the conversation (for example, whether someone responds with “uh-huh’s” or with silence). “It listens to the pattern of speech, not the words,” says Pentland, a scientific advisor to the company. “By measuring those signals in the background, you can tell what’s going on.”